Rice plant diseases are one of the main factors causing decreased productivity and threatening national food security. Farmers' limited knowledge in recognizing early symptoms of disease often leads to delays in treatment. The results of this research are educated in community service with the aim of developing and implementing Computer Vision-based technological innovation education to support an early warning system for rice diseases. The methods used include collecting rice leaf images in the field, digital image processing, and applying Computer Vision models to recognize visual patterns of disease symptoms. Educational activities with students are carried out through training and mentoring for farmers and agricultural extension workers regarding the use of this technology as an early detection tool. The expected results of this service are increased understanding and ability of users or partners in identifying rice diseases more quickly and accurately, so that they can support appropriate decision-making in disease control and increase rice agricultural productivity in a sustainable manner.
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